WEBVTT 1 00:00:00.440 --> 00:00:04.000 Extension two twenty four. Give her a call. That number 2 00:00:04.000 --> 00:00:08.359 again is nine oh nine eight A nine eight three 3 00:00:08.519 --> 00:00:11.279 seven seven extension two twenty four. 4 00:00:13.039 --> 00:00:15.800 You're listening to the Inland Talk Express ten fifty AM 5 00:00:15.839 --> 00:00:19.199 and one oh six point five FM CACAA, Loma, Linda. 6 00:00:20.000 --> 00:00:23.600 The information economy has a rid. The world is teeming 7 00:00:23.640 --> 00:00:27.839 with innovation as new business models reinvent every industry industry. 8 00:00:27.920 --> 00:00:32.240 Inside Analysis is your source of information and insight about 9 00:00:32.280 --> 00:00:34.799 how to make the most of this exciting new era. 10 00:00:35.079 --> 00:00:39.320 Learn more at inside analysis dot Comsideanalysis dot com. And 11 00:00:39.399 --> 00:00:42.200 now here's your host, Eric Kavanaugh. 12 00:00:46.799 --> 00:00:49.439 All Right, ladies and gentlemen, Hello and welcome back once 13 00:00:49.479 --> 00:00:51.840 again to the only coast to coast radio show that's 14 00:00:51.840 --> 00:00:55.039 all about the information economy. It's time for Inside Analysis. 15 00:00:55.159 --> 00:00:58.119 You're truly Eric Kavanaugh here, and I'm so excited to 16 00:00:58.159 --> 00:01:02.159 be talking about engineering these days, engineering for success. And 17 00:01:02.439 --> 00:01:05.200 what's one of the hot topics that we have, especially 18 00:01:05.239 --> 00:01:08.040 with all these electric vehicles and hybrid vehicles these days, 19 00:01:08.359 --> 00:01:12.079 are the batteries. And batteries of course are expensive, they're heavy. 20 00:01:12.560 --> 00:01:14.799 We want them to run as long as humanly possible. 21 00:01:14.920 --> 00:01:17.319 No one likes charging their batteries up people like using 22 00:01:17.319 --> 00:01:21.120 their batteries, and certainly in the electric vehicle world, they 23 00:01:21.159 --> 00:01:24.120 are crucially important. I mean, with a hybrid, you got gas. 24 00:01:24.159 --> 00:01:26.680 With an electric vehicle, all you have is the electricity 25 00:01:26.719 --> 00:01:29.840 and that's in the battery. It's very heavy, it's very expensive. 26 00:01:30.200 --> 00:01:32.239 So what can we do to improve the performance of 27 00:01:32.280 --> 00:01:35.359 these batteries. Well, guess what we've got. Jovanni Rossi calling 28 00:01:35.439 --> 00:01:37.480 it all the way from Milan, Italy, my favorite country 29 00:01:37.519 --> 00:01:40.040 in the world. I love Italy, and he is with 30 00:01:40.120 --> 00:01:43.640 a company called Electra. They are leaders and applied AI 31 00:01:43.799 --> 00:01:48.319 for battery packs. I'm like, what explain this? So, Giovanni, 32 00:01:48.400 --> 00:01:50.519 welcome to the show. Tell us a bit about what 33 00:01:50.560 --> 00:01:53.200 you folks are doing and how you're able to use 34 00:01:53.239 --> 00:01:57.159 a digital twin of batteries to improve the performance, and 35 00:01:57.239 --> 00:01:59.719 not just in the design phase, like meaning for the 36 00:01:59.760 --> 00:02:02.519 next set of batteries to come on the market, but 37 00:02:02.640 --> 00:02:04.760 for batteries that are already out there being used. Tell 38 00:02:04.799 --> 00:02:06.760 us what Electra is and how you're doing this stuff. 39 00:02:07.760 --> 00:02:08.360 Thank you, Eric. 40 00:02:08.439 --> 00:02:12.080 So, Electra is an AI clintech and B to B 41 00:02:12.199 --> 00:02:15.319 software company that is like focused to unlock the full 42 00:02:15.319 --> 00:02:19.199 potential of Barry technology. So basically as was mentioning. We 43 00:02:19.240 --> 00:02:22.000 have two different type of products. The first one is 44 00:02:22.039 --> 00:02:24.800 like a digital tween applications, so we study the barries, 45 00:02:24.879 --> 00:02:27.360 we understand what is happening, you know, between the berry 46 00:02:27.479 --> 00:02:30.879 with having a virtual replica of the battery where you 47 00:02:30.960 --> 00:02:34.960 can thanks to our software capability and AI models, test 48 00:02:35.199 --> 00:02:37.960 and innovate with the berry, so you can insert your 49 00:02:37.960 --> 00:02:42.080 different parameters. You can test out new chemistries or new 50 00:02:42.120 --> 00:02:45.479 models what you want to do, what is necessary to 51 00:02:45.520 --> 00:02:48.520 make a new berries, and so you can get faster 52 00:02:48.639 --> 00:02:51.680 to your results. Basically, you know, when you need to 53 00:02:51.800 --> 00:02:54.319 produce a new berries, it can take up to ten 54 00:02:54.400 --> 00:02:57.639 years and cost like up to one billion dollars, and 55 00:02:57.680 --> 00:03:01.199 so of course you need technology as ours to decrease 56 00:03:01.240 --> 00:03:03.840 of course your time and also your cost into making 57 00:03:03.879 --> 00:03:04.520 new berries. 58 00:03:05.000 --> 00:03:07.080 On the other side, we also have a set of 59 00:03:07.120 --> 00:03:07.800 software for. 60 00:03:07.840 --> 00:03:12.560 Like you know, managing, optimizing and controlling very capabilities and 61 00:03:12.599 --> 00:03:16.479 so improving again the performance of the berries and providing 62 00:03:16.560 --> 00:03:19.520 valuable insights for the different type of users and for 63 00:03:19.599 --> 00:03:22.960 the business managing these barries so to make the battery 64 00:03:23.120 --> 00:03:26.479 lasts longer and perform better and so maximizing of course 65 00:03:26.520 --> 00:03:28.680 the reternal investment for the battery assets. 66 00:03:29.840 --> 00:03:33.240 Yeah, that's really interesting. So and let's talk first about 67 00:03:33.400 --> 00:03:37.560 the digital twin and that environment where you have built 68 00:03:37.560 --> 00:03:42.280 out in a computing environment. Obviously the battery itself, what 69 00:03:42.439 --> 00:03:46.000 goes into it, and then you're able to allow your 70 00:03:46.439 --> 00:03:50.199 engineers to play around with different settings. Is it getting 71 00:03:50.240 --> 00:03:52.520 into the material science? Like how much detail can you 72 00:03:52.560 --> 00:03:55.319 give us on what's done in that environment and how 73 00:03:55.360 --> 00:03:58.719 you're enabling more efficient battery designs. 74 00:03:59.639 --> 00:04:03.400 Ye, can go into more than one hundred parameters, you know, 75 00:04:03.479 --> 00:04:06.719 into the very spects, so it can be either at 76 00:04:06.759 --> 00:04:08.680 a cell level and so like you know, into the 77 00:04:08.719 --> 00:04:12.520 small great stuff in that sense, into until like the 78 00:04:12.680 --> 00:04:14.840 very pack. So it depends of course of what we 79 00:04:14.919 --> 00:04:18.160 want to do. But we have different applications, different modules 80 00:04:18.160 --> 00:04:20.600 in the platform, and so you can go sell to 81 00:04:20.720 --> 00:04:24.040 pack to pack levels so that you can test and 82 00:04:24.079 --> 00:04:26.959 innovate whatever is like necessary for you. Of course you 83 00:04:27.000 --> 00:04:30.240 can change parameters. There are already some pre built AI 84 00:04:30.399 --> 00:04:33.319 model that you know, we have already designed and tested 85 00:04:33.680 --> 00:04:36.639 with different customers and understanding of course the trends in 86 00:04:36.680 --> 00:04:39.800 the market. But then of course we can also create 87 00:04:39.879 --> 00:04:44.519 some additional customized AI models to do some very specific 88 00:04:44.560 --> 00:04:46.360 operation that a customer may be doing. 89 00:04:48.319 --> 00:04:51.720 That's interesting. So with all these parameters, you're allowing the 90 00:04:51.800 --> 00:04:54.839 scientists basically to get in there and just play around 91 00:04:54.839 --> 00:04:57.839 with things and see about whether it's the kind of 92 00:04:57.839 --> 00:05:00.879 materials that are used, how much of them are used, 93 00:05:01.040 --> 00:05:04.959 all these different aspects of the actual design process. And 94 00:05:05.000 --> 00:05:08.279 then in this digital twin world you can kind of 95 00:05:08.279 --> 00:05:11.480 play around. Can you talk a bit about the accuracy, 96 00:05:11.720 --> 00:05:16.040 like what, you know, what's the range of efficacy with 97 00:05:16.240 --> 00:05:19.120 these tests when you do them in the digital twin 98 00:05:19.160 --> 00:05:21.759 world and then you see what happens in the real world. 99 00:05:21.839 --> 00:05:24.600 Is that something that you're capturing and managing over time 100 00:05:24.639 --> 00:05:25.439 the data around that. 101 00:05:26.519 --> 00:05:28.839 Yeah, I mean like you can play around with whatever 102 00:05:28.879 --> 00:05:30.920 it's like, you know, within the platform of course, and 103 00:05:30.959 --> 00:05:35.279 also adding some additional bodiles and piece when it is necessary. 104 00:05:35.800 --> 00:05:37.839 And I think that the main benefit. 105 00:05:37.519 --> 00:05:39.399 Here is like you know, when you need to test 106 00:05:39.560 --> 00:05:41.519 out some berries, you know, and you can have this 107 00:05:41.720 --> 00:05:44.519 digital replica and you can play around with it, you 108 00:05:44.560 --> 00:05:47.160 can decrease the testing time, so you know that that 109 00:05:47.240 --> 00:05:50.560 seems like a real deal. And the game changer perspective 110 00:05:50.600 --> 00:05:52.959 that is, like you know, you don't need to have 111 00:05:53.120 --> 00:05:55.920 like a lot of you know, physical testing, but you 112 00:05:55.959 --> 00:05:59.759 can do everything virtually and this can go up to 113 00:06:00.160 --> 00:06:03.480 you know, ninety percent of the testing can be reduced, 114 00:06:04.199 --> 00:06:06.920 of course in the best case scenario, but we have 115 00:06:07.000 --> 00:06:09.639 seen that an average can be of like reduction in 116 00:06:09.720 --> 00:06:13.199 test is like sixty to seventy percent, so meaning that 117 00:06:13.279 --> 00:06:15.160 of course you're saving up a lot of time and 118 00:06:15.160 --> 00:06:17.279 also a lot of money, and so the scientists can 119 00:06:17.319 --> 00:06:20.800 also focus on some more interesting stuff. Let's say this 120 00:06:20.879 --> 00:06:24.360 way than just replicate the test over and over again. 121 00:06:26.279 --> 00:06:28.839 You know, I remember talking to a gentleman, a very 122 00:06:28.959 --> 00:06:32.040 very interesting guy. He is an electric car racer, and 123 00:06:32.480 --> 00:06:35.040 we were over in Belgium for an electric car race 124 00:06:35.079 --> 00:06:37.360 a couple of years ago, and he was talking about 125 00:06:37.680 --> 00:06:43.720 this this effect when you float you can actually slowly 126 00:06:43.759 --> 00:06:46.360 you can actually increase the energy in the battery a 127 00:06:46.399 --> 00:06:47.920 little bit. Do you know about this? Like when you 128 00:06:47.959 --> 00:06:51.360 break our cost in an EV, the electric motor access 129 00:06:51.439 --> 00:06:54.879 kind of a generator converting the energy back into electrical energy. 130 00:06:54.920 --> 00:06:56.720 Is that right correct? 131 00:06:56.959 --> 00:06:59.639 Yeah? And you can say up plum energy and refiel 132 00:06:59.680 --> 00:07:00.560 that of the marry. 133 00:07:00.639 --> 00:07:03.319 Yeah, that's pretty cool. That's pretty cool stuff. And then 134 00:07:03.480 --> 00:07:07.279 talk about the battery management systems I'm getting spanked by 135 00:07:07.279 --> 00:07:09.160 the sunlight here in my head, but try not to 136 00:07:09.160 --> 00:07:12.639 worry about that. Talk about how you can also work 137 00:07:12.680 --> 00:07:17.360 with the management matteries I'm sorry, the battery management system 138 00:07:17.759 --> 00:07:19.600 to improve performance there. What does that look like? 139 00:07:21.000 --> 00:07:24.959 So basically, let's take the an electric vehicle as an example. 140 00:07:25.000 --> 00:07:28.319 You know what you do right now, It's like you 141 00:07:28.439 --> 00:07:31.279 have different information that are coming from the berries, coming 142 00:07:31.279 --> 00:07:34.120 from the driving style, coming from the environments, and of 143 00:07:34.120 --> 00:07:36.800 course all of these is like impacting the performance of 144 00:07:36.920 --> 00:07:37.360 the battery. 145 00:07:37.480 --> 00:07:40.040 So what we do is like we take all of. 146 00:07:39.920 --> 00:07:43.800 These information together, so berries, environment, driving style, and we 147 00:07:43.879 --> 00:07:48.360 put everything together, and thanks to our AI you know, algorithm, 148 00:07:48.600 --> 00:07:51.480 we can provide an output to the users, to the 149 00:07:51.560 --> 00:07:55.279 drivers in the sense that is like how you can optimize, 150 00:07:55.360 --> 00:07:58.959 of course your range. You can so extend your range 151 00:07:59.600 --> 00:08:05.759 in this sense we have been able to estimate that. 152 00:08:05.879 --> 00:08:11.240 Of course, the reduction of sorry, the average error in 153 00:08:11.319 --> 00:08:14.040 like you know, estimating the range is like twenty percent 154 00:08:14.560 --> 00:08:17.920 fifteen to twenty percents depend on vehicles. And with our 155 00:08:18.000 --> 00:08:20.680 model you can go down to less than one percent 156 00:08:20.879 --> 00:08:24.120 error in estimating range. So this means that of course 157 00:08:24.279 --> 00:08:28.360 you have much more precise information in that space, and 158 00:08:28.399 --> 00:08:31.399 we also you know, and with additional insights and suggest 159 00:08:31.600 --> 00:08:34.399 that we can provide, you can also extend the range 160 00:08:34.440 --> 00:08:38.480 and the capabilities. We have actually been testing these very 161 00:08:38.519 --> 00:08:43.600 recently in a cross country you know trip coming starting 162 00:08:43.600 --> 00:08:48.320 from Boston to Vegas, because we were presenting our technology 163 00:08:48.320 --> 00:08:51.159 at CS twenty thirty five, and we did it with 164 00:08:51.279 --> 00:08:54.720 like a Tesla cybertruck. So our founder, a core founder 165 00:08:54.759 --> 00:08:58.600 and CEO of Britain Martini, and one Copio drove all 166 00:08:58.600 --> 00:09:01.399 the way down from Boston to Vegas to demonstrate the 167 00:09:01.440 --> 00:09:03.480 capability for all our algorithms. 168 00:09:04.080 --> 00:09:04.799 That's Alloyd. 169 00:09:05.240 --> 00:09:06.679 Yeah, it's a very long drive. 170 00:09:06.840 --> 00:09:11.279 They looked like seven days, so that's really intense sad 171 00:09:11.360 --> 00:09:13.639 this way, and we have been able to you know, 172 00:09:13.679 --> 00:09:17.440 showcase and demonstrate that we can extend the range of 173 00:09:17.519 --> 00:09:22.000 twenty percent and reduce the charges of around thirty three percent. 174 00:09:22.759 --> 00:09:24.960 That is pretty it's a pretty good number, we say. 175 00:09:25.519 --> 00:09:27.559 And in all of these you know, also managing and 176 00:09:27.639 --> 00:09:31.320 understanding all the data coming from the various environmental driving styles, 177 00:09:31.320 --> 00:09:35.240 and of course we have also capability to predict failures 178 00:09:35.240 --> 00:09:37.519 in advance, so we can have like in a product 179 00:09:37.519 --> 00:09:40.559 that is like one hundred percent safe for of course 180 00:09:40.600 --> 00:09:44.320 the driver and and for them of course vehicle producer 181 00:09:44.360 --> 00:09:47.080 in that sense that is also very very interesting, and 182 00:09:47.360 --> 00:09:49.679 all of these can be scaled when you think not 183 00:09:49.720 --> 00:09:52.879 only you know individual drivers, but you have like fleets 184 00:09:53.000 --> 00:09:56.960 of vehicles or flit of electric vehicles, you know, adding 185 00:09:57.000 --> 00:09:59.799 all of these information and understanding what is happening within 186 00:09:59.840 --> 00:10:02.200 the so of course, what is like the state of 187 00:10:02.240 --> 00:10:05.039 hels of your battery, what is like the degradation of 188 00:10:05.120 --> 00:10:07.720 your batteries, and so how much your btrier can stay 189 00:10:07.879 --> 00:10:10.879 can last? You know, for what we define as the 190 00:10:10.879 --> 00:10:13.519 remain a useful life of a battery, you can actually 191 00:10:13.600 --> 00:10:17.120 increase the value of your asset up to forty percent. 192 00:10:18.080 --> 00:10:20.840 So that is like a way for both the drivers, 193 00:10:21.120 --> 00:10:23.240 the OEM or the battery producer. And then you know, 194 00:10:23.360 --> 00:10:28.279 the fleet operators to have many information, many sites and 195 00:10:28.639 --> 00:10:33.559 so have a much better capability to manage the operations 196 00:10:33.600 --> 00:10:36.240 and so of course get the value out of it. 197 00:10:37.120 --> 00:10:39.720 Yeah, well for sure. So I'm guessing what you're doing 198 00:10:39.879 --> 00:10:43.679 here is in terms of being able to optimize the 199 00:10:43.679 --> 00:10:49.440 battery life is you're you're analyzing the driving behavior. So 200 00:10:49.559 --> 00:10:52.559 does this person accelerate very quickly the drive? It very 201 00:10:52.600 --> 00:10:55.080 high speeds on a regular basis, do they go up 202 00:10:55.120 --> 00:10:57.679 and down often in terms of speed. These sorts of 203 00:10:58.120 --> 00:11:01.480 variations will have an impact on the battery life, and 204 00:11:01.559 --> 00:11:05.600 so what you can probably do is detect those algorithmically, 205 00:11:05.720 --> 00:11:10.000 understand what's really happening, and then give some recommendations to 206 00:11:10.039 --> 00:11:12.519 the user to say, hey, maybe if you were to 207 00:11:12.519 --> 00:11:15.360 not speed up and slow down so quickly, you would 208 00:11:15.360 --> 00:11:17.720 extend I'm just guessing here that you know, if you 209 00:11:17.799 --> 00:11:21.159 haven't even keel drive, you're going to get better use 210 00:11:21.240 --> 00:11:22.200 of the battery. 211 00:11:21.879 --> 00:11:24.759 Right, yes, and your mattery can last longer because it's 212 00:11:24.799 --> 00:11:28.159 not allly about range and performance, but it's like you know, 213 00:11:28.240 --> 00:11:30.600 if you drive better that sense, so if you use 214 00:11:30.639 --> 00:11:34.919 it battery better, your barrier can last for longer. Of course, 215 00:11:35.000 --> 00:11:38.639 we have some algorithms like optimizing how much the bettery 216 00:11:38.720 --> 00:11:41.039 can last. But of course then in this case, of 217 00:11:41.120 --> 00:11:44.360 course also the users like responsible of that. So you know, 218 00:11:44.519 --> 00:11:47.600 the two things combined that is like what can make 219 00:11:47.639 --> 00:11:50.679 you very lasts longer? And if you very lasts longer, 220 00:11:51.159 --> 00:11:53.080 you know, it means that you are keeping your cart 221 00:11:53.159 --> 00:11:56.639 longer in a way, and that's also saving money in 222 00:11:56.679 --> 00:12:00.039 a sense, but also results of some environmental impact that 223 00:12:00.200 --> 00:12:03.360 is definitely important in this sense. And of course you 224 00:12:03.360 --> 00:12:06.120 can scale these not only to electric vehicles, but if 225 00:12:06.120 --> 00:12:09.320 you think also stationary storage, that is like another application, 226 00:12:09.519 --> 00:12:11.720 usually much more for B to B side, let's say 227 00:12:11.720 --> 00:12:14.360 this way of leg for businesses, but it's also becoming 228 00:12:14.639 --> 00:12:20.080 quite popular for homes, especially you know, mentioning you know 229 00:12:20.159 --> 00:12:22.039 the B two B side, or like businesses, when you 230 00:12:22.039 --> 00:12:25.840 have some solar farms or wind farms and you want 231 00:12:25.879 --> 00:12:28.399 to store the excess of energy because you know, renewable 232 00:12:28.440 --> 00:12:31.639 energy is very cool, but you know the shine and 233 00:12:32.120 --> 00:12:35.480 the sun, sorry, it is not always shining and the 234 00:12:35.519 --> 00:12:38.399 wind is not always ploying, so you need to you know, 235 00:12:38.480 --> 00:12:41.039 to store the energy when when you have the excess 236 00:12:41.159 --> 00:12:44.399 of energy and then release it into the grid. And 237 00:12:44.440 --> 00:12:49.279 so having technological capabilities and aid I driven capability to 238 00:12:49.360 --> 00:12:52.600 understand what is happening in these berries, to manage them 239 00:12:52.639 --> 00:12:55.480 better and to optimize them, and also to predict falls 240 00:12:55.840 --> 00:12:58.600 because you know, having all of these information and it 241 00:12:58.639 --> 00:13:01.759 is one of the main game change capability about what 242 00:13:01.799 --> 00:13:04.320 technology is that we can predict falls up to three 243 00:13:04.360 --> 00:13:07.120 months in advance. So this means that we can understand 244 00:13:07.200 --> 00:13:09.399 what is actually happening, and you know how your berry 245 00:13:09.440 --> 00:13:11.840 is performing, and if you're going to have some critical faults, 246 00:13:11.919 --> 00:13:13.759 and when I mean criptical faults is like you know 247 00:13:14.559 --> 00:13:17.799 them a runaway or like fires or some other issue 248 00:13:17.799 --> 00:13:20.720 with a very that's very very important to maintain safety 249 00:13:20.759 --> 00:13:22.279 and reliability of that asset. 250 00:13:23.039 --> 00:13:24.960 Yeah, no, that that's very interesting. And there are also 251 00:13:25.000 --> 00:13:28.519 these power walls, right, doesn't Tesla don't they have a 252 00:13:28.559 --> 00:13:30.720 power wall? So basically you can buy a car, but 253 00:13:30.759 --> 00:13:33.200 you also buy this wall that is like in your house, 254 00:13:33.759 --> 00:13:36.759 and it's it's it is a long term battery storage 255 00:13:36.840 --> 00:13:37.759 is what it boils down to. 256 00:13:37.879 --> 00:13:38.039 Right. 257 00:13:38.080 --> 00:13:40.000 It allows you to I'm guessing to charge the car 258 00:13:40.120 --> 00:13:42.360 faster and do things of this nature. Yeah, you also 259 00:13:42.440 --> 00:13:45.039 just have a power source, like you mentioned, because I 260 00:13:45.639 --> 00:13:48.720 looked into solar panels years ago when we were in Texas, 261 00:13:49.159 --> 00:13:51.039 and you know, some of the key things you have 262 00:13:51.080 --> 00:13:54.440 to keep in mind are being able to manage that 263 00:13:54.559 --> 00:13:56.759 power that comes in and storage such that at a 264 00:13:56.840 --> 00:13:59.320 certain point you can then pump it back into the grid, right, 265 00:13:59.360 --> 00:14:01.039 which is you know, you have to be very delicate 266 00:14:01.080 --> 00:14:04.000 about that obviously, because it's electrical energy. You don't want 267 00:14:04.039 --> 00:14:06.519 to to get too much So what are you able 268 00:14:06.559 --> 00:14:10.279 to do there in terms of understanding the sort of 269 00:14:10.360 --> 00:14:14.159 dynamics of how battery usage works in these walls, and like, 270 00:14:14.279 --> 00:14:16.720 can you I presume you can extend their life too, right. 271 00:14:17.360 --> 00:14:18.759 Correct, we can extend the life. 272 00:14:18.759 --> 00:14:22.039 You can monitor them of course better and especially understanding 273 00:14:22.360 --> 00:14:27.080 how they are performing and increase their again performance and 274 00:14:27.159 --> 00:14:30.080 optimizing them so that you can have like more energy 275 00:14:30.120 --> 00:14:34.480 to use in that sense, and charging faster your car 276 00:14:34.519 --> 00:14:36.240 if it is a car for application for a car, 277 00:14:36.480 --> 00:14:39.159 or like you know, managing better d energy for your home. 278 00:14:39.840 --> 00:14:42.519 Optimizing of course also the a flow of energy because 279 00:14:42.600 --> 00:14:44.399 usually you have pav panels and so you want to 280 00:14:44.440 --> 00:14:47.639 have everything that is working in a very optimized way. 281 00:14:48.960 --> 00:14:52.360 That's very interesting. So do you get much traction in 282 00:14:52.360 --> 00:14:54.720 that space, or maybe talk a bit about your clients 283 00:14:54.759 --> 00:14:57.159 who's using this right now? To what effect? 284 00:14:57.159 --> 00:14:57.360 I mean? 285 00:14:57.360 --> 00:15:00.679 Obviously it's you're just extending the life of this asset, 286 00:15:01.159 --> 00:15:03.519 and you're improving the use of this asset, which is 287 00:15:03.559 --> 00:15:08.639 incredibly valuable and saves money and also saves you on trouble, 288 00:15:09.120 --> 00:15:12.000 especially this part about being able to predict fires, because 289 00:15:12.039 --> 00:15:14.840 that is the one real big downside, it seems to 290 00:15:14.879 --> 00:15:17.679 me of this whole paradigm is that these things can 291 00:15:17.720 --> 00:15:19.919 get too hot and just blow up and that there's 292 00:15:19.960 --> 00:15:24.080 no bueno, right, so what can you do happen? Yeah, so. 293 00:15:26.000 --> 00:15:28.840 We I mean like thanks to the technology that that 294 00:15:29.039 --> 00:15:32.600 is like a new layer I would say about understanding 295 00:15:32.639 --> 00:15:35.720 better these assets and using them better. I think that 296 00:15:35.799 --> 00:15:38.080 you know right now that are the right technology and 297 00:15:38.120 --> 00:15:42.399 also the artificial intelligence and machine learning capabilities to better 298 00:15:42.480 --> 00:15:46.320 understand how to again manage and optimize these assets. 299 00:15:46.960 --> 00:15:48.600 That will be also. 300 00:15:48.519 --> 00:15:51.360 You know, well we'll have we will have so much 301 00:15:51.639 --> 00:15:54.600 a broader adoption of these assets. And so this will 302 00:15:54.639 --> 00:15:58.639 also change the paradigm of how we think at energy 303 00:15:58.759 --> 00:16:01.279 in general and also the all the energy transition and 304 00:16:01.320 --> 00:16:04.200 everything is based on this because of course it's not 305 00:16:04.240 --> 00:16:06.480 only again the renewables, but you also need some other 306 00:16:06.840 --> 00:16:09.879 components to make this happen and also to sustain a 307 00:16:10.000 --> 00:16:15.000 much lower environmental impact, and so all of these will 308 00:16:15.000 --> 00:16:19.720 be much more necessary, especially technological side, for like making 309 00:16:19.759 --> 00:16:23.240 this transition you know, a reality. And if you think 310 00:16:23.799 --> 00:16:26.039 out the grid right now is like you know configure 311 00:16:26.080 --> 00:16:28.720 for instance, you know and you have like you know, 312 00:16:28.919 --> 00:16:32.080 the traditional system in the western countries, like you have 313 00:16:32.200 --> 00:16:34.720 big plants where you produce the energy and then it's 314 00:16:35.080 --> 00:16:38.519 distributed to like you know, to the grid, to different facilities. 315 00:16:38.559 --> 00:16:42.240 That is like off taking the energy right now with 316 00:16:42.480 --> 00:16:46.000 having you know, solar farms, wind farms and also you 317 00:16:46.039 --> 00:16:50.440 know BV panels in like domestic and business facility, so 318 00:16:50.519 --> 00:16:52.200 like for reastance on your rooftop or like you know, 319 00:16:52.200 --> 00:16:55.720 in some olar situations, you basically are changing this perspective 320 00:16:55.759 --> 00:16:58.720 and changing the paradigm of how the energy flows are 321 00:16:58.759 --> 00:17:02.200 actually you know, pumping in energy into the grid. And 322 00:17:02.240 --> 00:17:06.000 so you need again capabilities technological capabilities to keep everything 323 00:17:06.200 --> 00:17:11.319 working and running smoothly and also to have additional benefit 324 00:17:11.400 --> 00:17:12.960 to all the users involved. 325 00:17:13.400 --> 00:17:15.119 What's next? What are you guys working on now that 326 00:17:15.160 --> 00:17:16.759 we can expect in like a year or so. What's 327 00:17:16.759 --> 00:17:19.240 the next big push for you? Oh? 328 00:17:19.319 --> 00:17:21.680 I cannot share that I would like to, but that's 329 00:17:21.680 --> 00:17:24.599 a good Yeah, that's pretty funny. 330 00:17:25.880 --> 00:17:28.960 It is like yeah, yeah, I mean I can share. 331 00:17:28.960 --> 00:17:31.119 It's like, you know, we are implementing day after day 332 00:17:31.359 --> 00:17:34.559 our models and you know, understanding what are the new 333 00:17:34.960 --> 00:17:38.480 needs of the customer. And I think the most important 334 00:17:38.480 --> 00:17:40.480 stuff this is also part of my job is like 335 00:17:40.559 --> 00:17:43.480 getting ahead of the curve. So it's like what trends 336 00:17:43.599 --> 00:17:46.039 are going to be there in the next six, twelve, 337 00:17:46.160 --> 00:17:49.279 eighteen months and what we can do to address those 338 00:17:49.319 --> 00:17:51.759 in advanced So one of the things that we've always 339 00:17:51.799 --> 00:17:54.799 been able so is like understanding the trends before they 340 00:17:54.799 --> 00:17:58.039 happen and you know, getting something out before that moment 341 00:17:58.079 --> 00:17:59.559 so that we be leading. 342 00:18:01.680 --> 00:18:05.119 Well, this is fantastic. And the company is Elektra. That 343 00:18:05.160 --> 00:18:07.160 are you based in Italy or you're just in Italy? 344 00:18:07.200 --> 00:18:08.240 It's a company based in Italy. 345 00:18:08.359 --> 00:18:11.839 No, the company is based in Boston, Massachusetts, so the 346 00:18:11.880 --> 00:18:14.920 main edportter is there and then we also second European 347 00:18:14.960 --> 00:18:16.599 headquarter into in Italy. 348 00:18:17.480 --> 00:18:21.240 Excellent, Well, that sounds going to be great, great, great, 349 00:18:21.599 --> 00:18:24.440 great information, great content. I love what you guys are doing. 350 00:18:24.519 --> 00:18:26.799 Very cool. Look these guys up, Giovanni Rossi of Elektra. 351 00:18:26.960 --> 00:18:34.839 We'll be right back. You're listening to Inside Analysis. 352 00:18:37.359 --> 00:18:42.319 Welcome back to Inside Analysis. Here's your host, Eric Tavanaugh. 353 00:18:45.039 --> 00:18:47.799 All right, folks back here on Inside Analysis. Your host here, 354 00:18:47.880 --> 00:18:50.559 Eric Kavanaugh, and I'm very pleased to have another guest 355 00:18:50.640 --> 00:18:53.319 with us today. Timothy Baines is the founder of a 356 00:18:53.319 --> 00:18:57.519 company called Compatio, doing really interesting stuff they've built a 357 00:18:57.559 --> 00:19:02.200 whole platform for you could say configure price quote. Really 358 00:19:02.279 --> 00:19:07.079 it's a platform for managing compatibility hence the name of 359 00:19:07.160 --> 00:19:11.519 different products. So think electrical engineering or building materials, or 360 00:19:11.720 --> 00:19:14.079 anytime you need to bring a bunch of big pieces 361 00:19:14.079 --> 00:19:17.559 and parts together to create some whole like I think 362 00:19:17.599 --> 00:19:21.119 a car, for example, or any kind of complex machinery. 363 00:19:21.519 --> 00:19:24.160 You need to know are these parts compatible, do they 364 00:19:24.240 --> 00:19:28.039 work together? And then understand pricing and be able to 365 00:19:28.079 --> 00:19:30.400 figure out what to charge for these things. And they 366 00:19:30.400 --> 00:19:33.119 have a whole platform that does that, and they're focused 367 00:19:33.160 --> 00:19:34.680 on a couple of markets, but they can do all 368 00:19:34.759 --> 00:19:37.680 kinds of different stuff. But Timothy, what really struck my 369 00:19:37.880 --> 00:19:42.400 interest here is you mentioned this taxonomy, and if you would, 370 00:19:42.440 --> 00:19:44.519 can you tell us what you mean by a taxonomy 371 00:19:44.519 --> 00:19:47.039 and how does that fit into what Campatio does. 372 00:19:48.160 --> 00:19:51.480 Yeah, sure, Eric, So, first of all, I think it's 373 00:19:51.920 --> 00:19:53.960 important to understand that at the core, at the heart 374 00:19:53.960 --> 00:19:57.720 of our system is essentially a knowledge graph, and that 375 00:19:57.799 --> 00:20:02.240 knowledge graph sits on top of a decision taxonomy that 376 00:20:02.480 --> 00:20:06.440 within a given industry, let's say electrical switch gear for example, 377 00:20:06.559 --> 00:20:11.799 or industrial automation components, we have a very precise set 378 00:20:11.839 --> 00:20:16.319 of categories as far as what components are what, along 379 00:20:16.400 --> 00:20:24.039 with very high quality and very carefully engineered attributes on 380 00:20:24.200 --> 00:20:29.319 the products as well as product catalogs for different manufacturers. 381 00:20:29.359 --> 00:20:32.799 So together the taxonomy which is the categories and the attributes, 382 00:20:33.200 --> 00:20:35.359 as well as the rules on what the attributes are 383 00:20:35.359 --> 00:20:37.759 allowed to be, what data type, what is the range 384 00:20:37.960 --> 00:20:40.960 or even what is the picklist of values, that comprises 385 00:20:41.000 --> 00:20:44.799 the taxonomy, and then that gets hooked up to catalogs 386 00:20:44.839 --> 00:20:49.960 of products, and together those feed into our larger sort 387 00:20:50.000 --> 00:20:52.759 of layers of logic that is essentially a knowledge graph. 388 00:20:53.720 --> 00:20:53.960 Yeah. 389 00:20:54.000 --> 00:20:56.839 And the reason why that's important for our audience out 390 00:20:56.839 --> 00:21:00.480 there listening is that when you have this graph and 391 00:21:00.519 --> 00:21:06.440 you have this ontology, you are cataloging all these myriad 392 00:21:06.480 --> 00:21:09.319 parts of which there can be millions of different ones, 393 00:21:09.799 --> 00:21:13.799 in such a way as to facilitate the alignment over time. 394 00:21:14.160 --> 00:21:17.039 Because if you were to try to manually put those 395 00:21:17.039 --> 00:21:20.720 into a just traditional relational database or something, first of all, 396 00:21:20.759 --> 00:21:22.799 it would take forever a day, and second of all, 397 00:21:22.839 --> 00:21:24.920 it would not be performed at all, it would be 398 00:21:25.039 --> 00:21:28.319 very very slow, very painful. So by going this route 399 00:21:28.319 --> 00:21:33.119 of having a graph, a knowledge graph substrate with ontologies 400 00:21:33.160 --> 00:21:36.960 for particular industries or disciplines, if you will, you're really 401 00:21:37.000 --> 00:21:41.759